Differences between the observed sensitivity of the climate to greenhouse gas emissions and those predicted by computer models have been reconciled, according to a paper in Nature Climate Change. The graph is from the paper and shows comparison of modelled and observed climate sensitivity. Image courtesy: Nature Climate Change and the authors.

Estimates of climate sensitivity – crudely, the amount of warming we can expect from greenhouse gas emissions – have varied with historical data indicating a lower sensitivity that climate models suggest. A new study explains that this difference is because the comparison between models and data is not ‘like-with-like’ and that it disappears when a proper comparison is made. This work implies a warmer future

Differences between the observed sensitivity of the climate to greenhouse gas emissions and those predicted by computer models have been reconciled, according to a paper in Nature Climate Change.

Climate models suggest more warming than observational data reports but the new study says that this is because the comparison between models and observations is flawed and that when the comparison is done correctly the observations and models come into line.

The implication of the research, by climate scientist Mark Richardson of the Jet Propulsion Laboratory in California and colleagues, is that warming in the past was greater than we think and that future warming may be higher than we might expect from observations.

Observations suggest a range of climate sensitivity for a doubling of atmospheric carbon dioxide concentrations of between 1.0–4.0°C while computer models imply a range of between 2.0–5.6°C. The paper, entitled “Reconciled climate response estimates from climate models and the energy budget of Earth”, provides three explanations for this difference.

Three effects increase observed climate sensitivity

The largest effect is due to the partial geographical coverage of observational data particularly around the poles. When climate model outputs are analysed in the same way as observational data – that is with the same gaps – then the researchers report that the models run cooler by around 15 per cent.

The next largest effect is caused by the use of sea surface temperatures rather than air temperatures in the observational record. Observations of surface temperature depend partly on ship-based measurements which are from the ocean’s surface layer, which has been warming at a slightly slower rate than the air above it. If the climate models are analyzed using both sea and air temperatures rather than air temperatures alone, the temperature change is reduced by a little under 5%.

The final effect arises from the blending of air and sea temperatures in regions where the sea ice edge has changed. This effect is the most uncertain, but has the smallest impact; less than 5%.

“When combined, these three factors reduce the temperature change in the climate model outputs by about a quarter. The different handling of the temperature data between the models and observations therefore explains almost all of the difference between the estimates of climate sensitivity from models and observations,” co-author Kevin Cowtan writes in a web article describing this research.

This research also implies that historical observations of temperature – such as the UK Meteorological Office’s HadCRUT dataset, have underestimated global warming to date. Co-author Ed Hawkins of the University of Reading writes on his Climate Lab Book website that the “implications for understanding historical global temperature change are also significant. It is suggested that changes in global air temperature are actually ~24% larger than measured by the HadCRUT4 global temperature dataset”.

In a separate article published in Nature Climate Science, climate scientist Kyle Armour from the University of Washington, says that the findings of this research indicate that observation-based estimates of climate sensitivity “may be substantially higher than previously reported, aligning them more closely with the range simulated by climate models and raising the spectre of a very warm future”.

Abstract

Climate risks increase with mean global temperature, so knowledge about the amount of future global warming should better inform risk assessments for policymakers. Expected near-term warming is encapsulated by the transient climate response (TCR), formally defined as the warming following 70 years of 1% per year increases in atmospheric CO2 concentration, by which point atmospheric CO2 has doubled. Studies based on Earth’s historical energy budget have typically estimated lower values of TCR than climate models, suggesting that some models could overestimate future warming. However, energy-budget estimates rely on historical temperature records that are geographically incomplete and blend air temperatures over land and sea ice with water temperatures over open oceans. We show that there is no evidence that climate models overestimate TCR when their output is processed in the same way as the HadCRUT4 observation-based temperature record. Models suggest that air-temperature warming is 24% greater than observed by HadCRUT4 over 1861–2009 because slower-warming regions are preferentially sampled and water warms less than air. Correcting for these biases and accounting for wider uncertainties in radiative forcing based on recent evidence, we infer an observation-based best estimate for TCR of 1.66°C, with a 5–95% range of 1.0–3.3°C, consistent with the climate models considered in the IPCC 5th Assessment Report.